Crowd V-IoE: Visual Internet of Everything Architecture in AI-Driven Fog Computing
Fog computing has emerged as a unifying platform to provide computing, communication, and storage for a variety of mobile applications. That helps achieve high bandwidth, high intelligence, low latency, and low energy consumption in handling massive networking devices and emerging rich multimedia se...
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Veröffentlicht in: | IEEE wireless communications 2020-04, Vol.27 (2), p.51-57 |
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creator | Ji, Wen Liang, Bing Wang, Yuqin Qiu, Rui Yang, Zheming |
description | Fog computing has emerged as a unifying platform to provide computing, communication, and storage for a variety of mobile applications. That helps achieve high bandwidth, high intelligence, low latency, and low energy consumption in handling massive networking devices and emerging rich multimedia services in 5G networks. Current prominence and future promises are changing from the Internet of Things (IoT) to the Internet of Everything (IoE), which is a union of people, process, data, and things. However, the development of fog radio access networks (F-RANs) is challenged by the diversity of IoE, ultra-high-definition videos on demand from users, and low-latency requirement of heterogeneous IoT devices. In this article, we present an architecture of visual IoE (V-IoE) in F-RANs. We systemically analyze the key challenges of V-IoE from the perspective of F-RANs, and propose a crowd V-IoE architecture. Through experimental results, we demonstrate that our proposed architecture exhibits better performance with lower bandwidth requirement, lower energy consumption, and lower latency in F-RANs. Finally, we conclude with a discussion of potential directions. |
doi_str_mv | 10.1109/MWC.001.1900349 |
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(IEEE) 2020</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>true</woscitedreferencessubscribed><woscitedreferencescount>24</woscitedreferencescount><woscitedreferencesoriginalsourcerecordid>wos000532257900007</woscitedreferencesoriginalsourcerecordid><citedby>FETCH-LOGICAL-c355t-597f3dd3aa0c0b159d7e700406175fed564a6456b4d5678c988fa5679c1b4a3a3</citedby><cites>FETCH-LOGICAL-c355t-597f3dd3aa0c0b159d7e700406175fed564a6456b4d5678c988fa5679c1b4a3a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9085263$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>315,781,785,797,27928,27929,54762</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9085263$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Ji, Wen</creatorcontrib><creatorcontrib>Liang, Bing</creatorcontrib><creatorcontrib>Wang, Yuqin</creatorcontrib><creatorcontrib>Qiu, Rui</creatorcontrib><creatorcontrib>Yang, Zheming</creatorcontrib><title>Crowd V-IoE: Visual Internet of Everything Architecture in AI-Driven Fog Computing</title><title>IEEE wireless communications</title><addtitle>WC-M</addtitle><addtitle>IEEE WIREL COMMUN</addtitle><description>Fog computing has emerged as a unifying platform to provide computing, communication, and storage for a variety of mobile applications. 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subjects | Applications programs Artificial intelligence Bandwidths Cloud computing Computer architecture Computer Science Computer Science, Hardware & Architecture Computer Science, Information Systems Crowdsourcing Edge computing Electronic devices Energy consumption Engineering Engineering, Electrical & Electronic High definition Internet of Things Mobile computing Multimedia Network latency Science & Technology Streaming media Technology Telecommunications Videos Wireless networks |
title | Crowd V-IoE: Visual Internet of Everything Architecture in AI-Driven Fog Computing |
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